Sales Forecasting in MRPeasy – AI-powered Production Planning for SMEs

MRPeasy has introduced Sales Forecasting, a new feature that helps manufacturers estimate expected sales quantities from historical customer order data, thus enabling more intuitive production and procurement planning.

What is Sales Forecasting in MRPeasy?

MRPeasy’s Sales Forecasting is a brand-new AI-powered feature that enables estimating upcoming production demand based on historical customer order data. Coupled with the Master Production Schedule functionality, this provides MRPeasy users with an effective way to gauge future demand for product quantities and align them precisely with production and procurement plans.

Sales forecasting in MRPeasy focuses on expected product quantities based on past customer orders. This makes the new feature a practical demand-planning tool for manufacturers that helps estimate how many units of each product customers are likely to need, so those quantities can be used to inform production and purchasing decisions for future periods.

Why forecasting matters for small manufacturers

Even small changes in demand can quickly affect your production schedules, stock levels, and purchasing timelines, all of which affect the precision of your delivery promises. Accurate forecasting turns historical sales patterns into a reliable planning input, reducing guesswork across your business.

More confidence in production planning

Accurate sales forecasting enables you to make informed decisions on production and inventory based on likely demand, rather than guessing volumes and only finding out as confirmed orders arrive. This insight simplifies decisions like what to make next, when to start purchasing materials, and whether the current capacity is enough for the months ahead.

For example, if one of your standard products sees a seasonal increase in early summer, a forecast for the item helps prepare materials and production time earlier, rather than reacting only once orders are already fully booked.

Reduced stockouts and excess inventory

The sales forecast also helps you optimize inventory levels closer to what customers are actually likely to need. This gives you more time to stock up on products with growing demand and avoid tying up too much cash in those with slowing sales.

This is especially useful if you manage both faster- and slower-moving products within the same inventory. Instead of applying the same purchasing logic to every item, you can now use forecasted quantities to make more targeted stock and replenishment decisions and set smarter reorder quantities.

Improved purchasing and material planning

Seeing expected product quantities earlier gives you a better chance to plan purchasing before demand becomes urgent.  There’s more time to check supplier lead times, place purchase orders earlier, and make sure the required materials are available when production needs them. As a result, purchasing becomes less reactive, and production is less likely to be delayed by missing parts.

For example, if a forecast shows higher expected demand for a product that uses a long-lead-time component, you can start procurement earlier and reduce the risk of delaying production because a key part is missing.

Planning is less dependent on manual methods

If you’re still using spreadsheets or other offline tools to estimate future demand, every update creates manual work and version-control issues. A built-in forecasting tool keeps demand planning closer to your actual customer order history, swapping your disconnected planning files with a data-driven automated workflow.

How the Sales Forecasting feature works in MRPeasy

Sales Forecasting is available in MRPeasy’s Enterprise and Ultimate tiers. The feature is a part of the CRM module and allows you to create individual forecasts for one or more of your products. The process is straightforward. Simply choose a forecast name, select the first month, set the forecast horizon (time period), and add the products you want to include.

The forecast horizon can be set to 3, 6, 12, or 18 months, and the starting month can be set up to two years in the future. Each forecast can include up to 100 products.

MRPeasy generates forecast values automatically using historical customer order data. The calculation is based on ordered quantities and delivery dates, while quotations and canceled orders are excluded. If a new product lacks at least 3 months of non-empty historical sales data, the system flags it as lacking historical data. You can still enter forecast values manually for these products, however.

Editing and reviewing the forecast

Forecast values are shown in a product-by-month input table. Each product has its own row, and each month in the forecast period has its own column, so you can review, enter, or adjust expected quantities directly.

The table provides a General view that shows forecast values, and a Detailed view that adds context like actual sales quantities, previous-year values, and year-on-year change. If your market research says the numbers should be different, checking and adjusting the AI-generated forecast is seamless.

Forecast overview and trend comparison

The Forecast overview section summarizes the forecast for a selected product. You can review totals grouped by configurable periods and compare changes against previous periods or previous-year values.

This helps quickly notice whether expected demand is increasing, decreasing, or following seasonality patterns. When calendar-year grouping is selected, MRPeasy can also show the estimated year total by combining actual sales from months that have already passed with forecasted future sales for the remaining months.

Watch the demo video for Sales Forecasting in MRPeasy.

Connecting sales forecasts with the Master Production Schedule

Perhaps the biggest planning value lies in linking your sales forecasts to MRPeasy’s Master Production Schedule (MPS). Once linked, the forecasted quantities populate the Sales forecast row in the MPS for the selected product, streamlining production and procurement planning around expected demand.

To use forecasts in the MPS, select a non-expired forecast for the appropriate product from the Sales forecast row. The row is then populated with values from the forecast, linking back to the forecast details page. If you manually change forecast values in the MPS, the forecast is automatically unlinked, helping to clarify whether the plan is still based on the original forecast or has been manually adjusted.

See our MPS demo video for detailed info on the Master Production Scheduling functionality.

What types of businesses can benefit from production forecasting

Make-to-stock manufacturers are typically most reliant on accurate forecasting. If your projected numbers are too conservative, you risk stockouts and missed sales. But overshooting sales projections can hurt as much as your cash gets tied up in excess finished goods and materials. Forecasting helps compare expected demand with previous periods and prior-year numbers, so seasonal shifts and market trends are easier to catch before they turn into stock problems.

While make-to-order and assemble-to-order companies don’t use forecasts to produce stock in advance, they still benefit from supporting better planning. Even though manufacturing is triggered only when an order comes in, recurring product families, subassemblies, raw materials, and shared workstations still need to be planned in advance. Visibility into which products are likely to drive demand in the coming months makes decision-making around purchasing, supplier follow-up, capacity, and delivery promises a lot easier.

For distributors and retailers, forecasting is mostly about smarter replenishment. Instead of relying only on current stock levels or last month’s orders, forecasts enable the use of customer order history to estimate what might be needed next. Forecast dashboards are especially helpful when you manage many SKUs, seasonal items, or products that move at very different speeds.

Increasing the forecasting accuracy further

• Use the forecast as a baseline, not the end-all. A good forecast narrows the range of likely demand, but it doesn’t remove uncertainty. Review the suggested quantities against what you know about your customers, seasonality, upcoming deals, supplier issues, or larger one-off orders. You don’t need to predict the future perfectly – the goal is to make better production and purchasing decisions earlier.
• Double-check every forecast, triple-check slower sellers. Stable, high-volume products are usually easier to forecast than slow-moving, seasonal, or highly customized items. For standard products with repeat demand, the AI-generated forecast is likely to provide a useful starting point. For intermittent or project-based demand, manual review is much more important because a few unusual orders can distort the picture.
• Compare forecasts with actuals and previous-year sales. The Detailed forecast helps you check whether the forecast makes sense next to real sales history and last year’s same period. This is useful for spotting seasonality, market trends, or products where demand is shifting to new patterns. If the number looks technically correct but seems commercially unrealistic, adjust it.
• Keep lead times and capacity in mind. Forecast accuracy matters more when the planning decision has to be made early. A product that uses long-lead-time materials or limited work center capacity should be reviewed more carefully than one that can be replenished or produced quickly.
• Review manual changes over time. Manual edits are useful when you know something reliably that the system doesn’t have data for. But editing should not become guesswork in a different form. If manual adjustments consistently improve your plan, they’re adding value. If not, it’s better to rely more on order history and use manual changes only for very clear business reasons.

Frequently asked questions (FAQ)

How does Sales Forecasting affect production planning?

Sales Forecasting gives you expected product quantities that can be used before customer orders are confirmed. When a forecast is linked to the Master Production Schedule, those quantities populate the Sales forecast row in the MPS, helping you plan production and procurement around likely demand. This makes the forecast actionable instead of leaving it as a separate planning estimate.

Do I still need to review the forecast manually?

Yes. AI-generated forecasts are useful starting points, but they should still be checked against what you know about customers and their behavior, seasonality, market conditions, larger upcoming orders, and external factors. The best results come from combining system-generated estimates with practical business judgment.

Which products are usually the most important to forecast?

Start with products where planning mistakes are expensive, like high-volume items, seasonal products, long-lead-time products, and items that use constrained materials or work centers. Slow-moving or highly customized products may still be worth forecasting, but they usually need more manual review.

Can Sales Forecasting help if I mostly manufacture to order?

Yes, but the value derived is usually different from make-to-stock production. MTO and ATO companies don’t generally use forecasts to build finished goods in advance, but they can still use expected demand based on past sales performance to plan common materials, subassemblies, supplier follow-up, and available production capacity.

Is sales forecasting the same as demand forecasting?

Sales forecasting and demand forecasting are often used interchangeably, but they usually mean slightly different things. Sales forecasting focuses on predicting sales revenue, close rate, and future performance, while demand forecasting estimates production demand within manufacturing processes. MRPeasy’s new functionality is closer to classical demand forecasting as it helps estimate how many units of each product customers are likely to need based on past sales data.

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